Description Usage Arguments Value See Also Examples
View source: R/compute.sigma.star.R
This function computes the intermediate correlation matrix by combining tetrachoric correlation for binary-binary combinations, biserial correlations for binary-normal combinations and Pearson correlation for normal-normal combinations. If the resulting correlation matrix is not positive definite, a nearest positive matrix will be used.
1 2 | compute.sigma.star(no.bin, no.nor, prop.vec.bin = NULL,
corr.vec = NULL, corr.mat = NULL)
|
no.bin |
Number of binary variables |
no.nor |
Number of normal variables |
prop.vec.bin |
Probability vector for binary variables |
corr.vec |
Vector of elements below the diagonal of correlation matrix ordered columnwise |
corr.mat |
Specified correlation matrix |
sigma_star |
A resulting intermediate correlation matrix Σ^* |
nonPD |
If a resulting intermediate correlation matrix is non-positive definite, it is stored in this value. Otherwise it is NULL. |
PD |
TRUE if Σ^* is positive definite, FALSE otherwise. A FALSE indicates that the nearest positive definite matrix is returned. |
eigenv |
Eigenvalues of the Σ^* before the conversion |
validation.corr
, nearPD
, phi2poly
, is.positive.definite
,
jointly.generate.binary.normal
, simulation
1 2 3 | cmat = lower.tri.to.corr.mat(corr.vec= c(0.16, 0.04, 0.38, 0.14, 0.47, 0.68),4)
compute.sigma.star(no.bin=2, no.nor=2, prop.vec.bin=c(0.4,0.7),
corr.vec=NULL,corr.mat=cmat)
|
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